Search Results for author: Benjamin Lambert

Found 4 papers, 0 papers with code

Improving Uncertainty-based Out-of-Distribution Detection for Medical Image Segmentation

no code implementations10 Nov 2022 Benjamin Lambert, Florence Forbes, Senan Doyle, Alan Tucholka, Michel Dojat

In this work, we evaluate various uncertainty frameworks to detect OOD inputs in the context of Multiple Sclerosis lesions segmentation.

Image Segmentation Medical Image Segmentation +2

Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis

no code implementations5 Oct 2022 Benjamin Lambert, Florence Forbes, Alan Tucholka, Senan Doyle, Harmonie Dehaene, Michel Dojat

The full acceptance of Deep Learning (DL) models in the clinical field is rather low with respect to the quantity of high-performing solutions reported in the literature.

Beyond Voxel Prediction Uncertainty: Identifying brain lesions you can trust

no code implementations22 Sep 2022 Benjamin Lambert, Florence Forbes, Senan Doyle, Alan Tucholka, Michel Dojat

Deep neural networks have become the gold-standard approach for the automated segmentation of 3D medical images.

Leveraging 3D Information in Unsupervised Brain MRI Segmentation

no code implementations26 Jan 2021 Benjamin Lambert, Maxime Louis, Senan Doyle, Florence Forbes, Michel Dojat, Alan Tucholka

Learning is performed using a multicentric dataset of healthy brain MRIs, and segmentation performances are estimated on White-Matter Hyperintensities and tumors lesions.

MRI segmentation Unsupervised Anomaly Detection

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